如何在Matplotlib的3D图中用箭头表示特征向量方向？

import numpy as np
from matplotlib import pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
from matplotlib.patches import FancyArrowPatch
from mpl_toolkits.mplot3d import proj3d

class Arrow3D(FancyArrowPatch):
    def __init__(self, xs, ys, zs, *args, **kwargs):
        FancyArrowPatch.__init__(self, (0,0), (0,0), *args, **kwargs)
        self._verts3d = xs, ys, zs

    def draw(self, renderer):
        xs3d, ys3d, zs3d = self._verts3d
        xs, ys, zs = proj3d.proj_transform(xs3d, ys3d, zs3d, renderer.M)
        self.set_positions((xs[0],ys[0]),(xs[1],ys[1]))
        FancyArrowPatch.draw(self, renderer)

# ... (假设您已计算出特征向量 eig_vec 和数据中心点 mean_x, mean_y, mean_z) ...

fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')
# ... (绘制您的3D散点图) ...

for v in eig_vec:
    a = Arrow3D([mean_x, mean_x + v[0]], [mean_y, mean_y + v[1]],
                [mean_z, mean_z + v[2]], mutation_scale=20,
                lw=2, arrowstyle="-|>", color="r")  #调整lw和mutation_scale控制箭头粗细和大小
    ax.add_artist(a)

# ... (其余绘图代码) ...
plt.show()